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Covariance in Multigroup and Few Group Reactor Physics Uncertainty Calculations

<p>Simulation plays a key role in nuclear reactor safety analysis and being able to assess the accuracy of results obtained by simulation increases their credibility. This thesis examines the propogation of nuclear data uncertainties through lattice level physics calcualtions. These input uncertainties are in the form of covariance matrices, which dictate the variance and covariance of specified nuclear data to one another. These covariances are available within certain nuclear data libraries, however they are generally only available at infinite dilution for a fixed temperature. The overall goal of this research is to examine the importance of various applications of covariance and their associated nuclear data libraries, and most importantanly to examine the effects of dilution and self-shielding on the results. One source of nuclear data and covariances are the TENDL libraries which are based on a reference ENDF data library and are in continuous energy. Each TENDL library was created by randomly perturbing the reference nuclear data at its most fundamental level according to its covariance. These perturbed nuclear data libraries in TENDL format were obtained and NJOY was used to produce cross sections in 69 groups for which the covariance was calculated at multiple temperatures and dilutions. Temperature was found to have little effect but covarances evaluated at various dilutions did differ significantly. Comparisons of the covariances calculated from TENDL with those in SCALE and ENDF/B-VII also revealed significant differences. The multigroup covariance library produced at this stage was then used in subsequent analyses, along with multigroup covariance libraries available elsewhere, in order to see the differences that arise from covariance library sources. Monte Carlo analysis of a PWR pin cell was performed using the newly created covariance library, a specified reference set of nuclear data, and the lattice physics transport solver DRAGON. The Monte Carlo analysis was then repeated by systematically changing the input covariance matrix (for example using an alternative matrix like that included with the TSUNAMI package) or alternate input reference nuclear data. The uncertainty in k-infinite and the homogenized two group cross sections was assessed for each set of covariance data. It was found that the source of covariance data as well as dilution had a significant effect on the predicted uncertainty in the homogenized cell properties, but the dilution did not significanty affect the predicted uncertainty in k-infinite.</p> / Master of Applied Science (MASc)

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/13396
Date10 1900
CreatorsMcEwan, Curtis E.
ContributorsNovog, David, Engineering Physics and Nuclear Engineering
Source SetsMcMaster University
Detected LanguageEnglish
Typethesis

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